Impactful data science at Pfizer depends largely on having access to the right data, tools, and a network of subject matter experts who can help turn a business problem or scientific question into actionable analytical insights. In this talk (originally held for students and faculty atStevens Institute of Technology, a Dataiku Academics partner), Neil Patel, interactive analytics and data visualization team lead at Pfizer, and Kristina Cheng, data scientist on the AI insights team at Pfizer, will discuss a day in the life of a data scientist at Pfizer, focusing on the end-to-end analytics process and the various ways in which collaboration occurs at every step.
Check out the full video below to discover:
Pfizer's journey to building data science capabilities to deliver business value, touching on data science talent, tools and technology (including Dataiku), and domain expertise
Ways data science can transform healthcare and pharmaceutical delivery (i.e., timelier detection and treatment, interaction data mining from doctor and patient engagement)
How Pfizer uses collaboration as part of the data science process, including their iterative framework across people, processes, and technology
Real-world examples of how data scientists understand a problem at hand and define the scope of the project (i.e., when to take a predictive or descriptive analytics approach)
How the team uses Dataiku as part of its analytics workbench to collaborate on data projects across user types (fast forward to 26:15 for this!)
Go Further on AI in Pharmaceuticals
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